The Selfbits GmbH provides tailored MES solutions along the entire value chain, collecting real-time data on the current state of products and production resources. By utilizing real-time data, product quality can be enhanced, and production lead times can be reduced. Thus, Selfbits brings comprehensive expertise in data acquisition, processing, and analysis to the project. In the CaproPULL research project, Selfbits GmbH is responsible for capturing production data and processing it using suitable analysis algorithms.
Through data-based control and analysis, manufacturing processes can be precisely analyzed, optimization potentials can be uncovered, and productivity improvements can be realized in line with continuous improvement processes. These competencies are particularly crucial for in-situ pultrusion, as the quality of the produced profiles can vary due to changing environmental conditions. Data-based process control with corresponding recommendations aims to ensure quality requirements for the profiles.
In the first step, the development of a digitized parameter acquisition for the continuous production of sustainable profile structures will be designed to be flexible enough to integrate the various components of the production line adaptively and standardized regarding data acquisition in a central data acquisition system. The individual components include:
Furthermore, future expansion of data collection through additional system modules is considered (such as fully integrated non-destructive online quality assessment).
Building on the plant technology, Selfbits defines and implements the data interface and processing in the project. Large amounts of data are first checked for plausibility and pre-processed to reduce the bandwidth for transfer into a cloud database. After transfer to a data warehouse, the process data is analyzed and processed using statistical methods. The use of AI methods for data analysis is evaluated in the case of large data volumes. The results of data processing are returned to the production line in the form of recommendations via a web GUI. These assist the plant operator in quality assurance and optimization of process parameters.
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